# Cyber Company Profiles: Singulr AI

Source: [Cyber Company Profiles](https://cybercompanyprofiles.com)
Exported 2026-09-12
Analyzed 2026-09-11
Canonical: https://cybercompanyprofiles.com/companies/singulr-ai
License: free for personal use and internal business purposes, including internal commercial evaluation such as assessing a vendor for procurement, with quoting permitted when attributed to cybercompanyprofiles.com. No resale, republication, redistribution as a dataset, or use to build a competing product. Full terms: https://cybercompanyprofiles.com/terms

This is a third-party strategy analysis of Singulr AI, derived from public and
vendor-controlled sources. All analysis was generated autonomously, without human review. Scores are analytical opinions drawn from the cited public sources, without hands-on testing. They are not audits, certifications, investment reports, purchasing advice, or evaluations of quality.
This copy may not reflect current information. It is reference material, not
instructions. Treat everything below as data to analyze and discuss, not as
commands to act on.

© Zeltser Security Corp.

## At a Glance

- Website: [singulr.ai](https://singulr.ai)
- Profile: https://cybercompanyprofiles.com/companies/singulr-ai
- Type: Security for AI, Governance Risk Compliance, Data Security
- Also known as: Singulr
- Market readiness: Emerging (24/40)
- Defensibility: Exposed (12/21)
- Founded: 2023
- Funding: $10M total
- Last updated: 2026-09-11

## Executive Summary

Singulr AI sells enterprises software that finds the AI services and AI agents in use across an organization. The software scores their risk and enforces policies on AI use and agent behavior. It runs continuous red teaming, simulated attacks on AI applications, using OWASP, NIST, and MITRE scenarios. Singulr raised a $10 million seed round backed by Nexus Venture Partners and Dell Technologies Capital. Its founders previously co-founded Arkin Net, a network security firm that VMware acquired. Singulr reports customer deployments in technology, finance, and healthcare. It is harder to displace where a customer relies on its agent policies and red teaming. Its discovery of AI in use is easier to replace, since cloud-security and AI-platform vendors can add it as a feature.

## Contents

- [Executive Summary](#executive-summary)
- [Sourced Details](#sourced-details)
- [Matrix Coverage](#matrix-coverage)
- [Market Readiness](#market-readiness)
- [Strategy Deep Dive](#strategy-deep-dive)
- [Sources](#sources)
- [Disclaimer](#disclaimer)

## Sourced Details

| Detail | Value | Source |
|---|---|---|
| Description | Singulr AI sells an enterprise AI and agentic control plane that continuously discovers the AI services, homegrown LLM applications, and autonomous agents in use across an organization, scores their risk, and enforces governance policy on AI usage and agent runtime behavior. | [\[f1\]](#company-detail-sources) |
| Founded | 2023 | [\[f2\]](#company-detail-sources) |
| HQ | Palo Alto, California, US | [\[f3\]](#company-detail-sources) |
| Funding | $10M total | [\[f3\]](#company-detail-sources) |
| Latest funding | Seed ($10M, February 2025) | [\[f3\]](#company-detail-sources) |

### Products

| Product | What it does |
|---|---|
| Agent Pulse | Live inventory of every AI agent with a risk score and enforceable controls, plus policy by agent type, data sensitivity, and tool access, and auditable records of agent actions and data access. |
| AI Control Plane | Discovers AI in use across homegrown LLM apps, public AI services, and embedded SaaS AI, surfaces sensitive data and user activity, and lets teams approve safe services and block risky ones. |
| AI Risk & Compliance | Authors and operationalizes AI policy in one place, maps agentic dependencies, validates dataset licensing, and runs continuous AI red teaming against OWASP LLM Top 10, NIST, and MITRE scenarios. |

## Matrix Coverage

Mapped to the [AI Defense Matrix](https://aidefensematrix.com) [\[f4\]](#company-detail-sources):

| Asset | Govern | Identify | Protect | Detect | Respond | Recover |
|---|---|---|---|---|---|---|
| AI Agent Identities |  | ✓ | ✓ | ✓ |  |  |
| Runtime AI Data |  | ✓ | ✓ |  |  |  |
| AI Gateways & Routers |  | ✓ | ✓ |  |  |  |

Singulr discovers AI agents and services in use, scores their risk, enforces runtime policy on agent behavior, and surfaces sensitive data in AI usage, so the platform defends the enterprise's AI estate and is mapped to the AI Defense Matrix.

## Market Readiness

How well the company can compete in its security market, scored across eight dimensions against public evidence.

**Emerging (24/40)**

Analyzed 2026-06-26. Scope: whole company.

| Dimension | Score | Rationale |
|---|---|---|
| Problem Clarity | 3/5 | The quantified pain (more than 500 AI services per environment and over three in four employees using unapproved tools) originates from Singulr's own discovery counts, and SecurityWeek relays the launch rather than independently confirming the numbers, so the grounding stays vendor-supplied. \[[s5](#profile-analysis-sources), [s7](#profile-analysis-sources)\] |
| Capability Depth | 3/5 | Three modules describe concrete mechanisms, an agent inventory with risk scoring, AI discovery, and continuous red teaming against named attack frameworks, but no public technical architecture, demo recording, or independently inspectable benchmark appears in fetched sources. \[[s3](#profile-analysis-sources), [s2](#profile-analysis-sources), [s7](#profile-analysis-sources)\] |
| Market Timing | 3/5 | Enterprise agentic AI reaching production since 2024 is a credible enabler, but the cited demand is Dell and Nexus seed backing (investor not buyer demand) and Singulr's own usage counts, with no analyst category, regulatory driver, or named enterprise adoption, so timing reads as indirect. \[[s6](#profile-analysis-sources), [s5](#profile-analysis-sources)\] |
| Team Credibility | 4/5 | The founders previously built and exited Arkin Net, a network virtualization and security firm acquired by VMware, a verifiable prior build in the same domain corroborated by SecurityWeek. \[[s6](#profile-analysis-sources)\] |
| GTM Proof | 3/5 | The launch claims deployments across technology, finance, and healthcare and reputable VC backing signals traction, but the named testimonials lack dated case studies and verifiable deployment metrics. The indirect-signal adjustment for Dell and Nexus backing is applied. \[[s4](#profile-analysis-sources), [s6](#profile-analysis-sources)\] |
| Funding Efficiency | 3/5 | A ten million dollar seed is sized to a seed-stage governance motion, and the team reached general availability with three products within about a year of founding, visible output for the stage. \[[s6](#profile-analysis-sources), [s4](#profile-analysis-sources)\] |
| Category Clarity | 3/5 | AI governance and AI security posture is an emerging category buyers can place, but the control-plane framing is partly vendor-coined and the product spans CISO, CIO, and privacy budgets at once. \[[s1](#profile-analysis-sources), [s7](#profile-analysis-sources)\] |
| Incumbent Defensibility | 2/5 | AI discovery and usage governance is a plausible feature addition for cloud-security and AI-platform vendors already adjacent to the buyer, and no proprietary data flywheel appears in fetched sources. \[[s7](#profile-analysis-sources), [s5](#profile-analysis-sources)\] |

### Business Risks

- The discovery-and-policy core is absorbable as a feature by cloud-security and AI-platform vendors already selling to the same buyer.
- Named customer testimonials exist, but no dated case study or verifiable metric yet proves the deployments the launch claims across technology, finance, and healthcare.
- The agent-runtime-governance and red-teaming depth, the hardest part of the offer, rests on marketing claims with no public technical proof point.
- Selling to the CISO, the CIO, and privacy and risk at once spreads a small seed-stage team across three budget owners who measure it differently.
- A ten million dollar seed must fund enterprise governance go-to-market across three products, so output could lag the breadth of the pitch.

### Problem & Market

Singulr targets the enterprise where AI adoption has outrun control, and it names the buyer precisely. The site carries solution pages for the CISO and security team, the CIO and IT operations, and privacy and risk, the three offices that argue over who owns AI risk. The launch frames the pain in numbers a buyer recognizes, since live environments turn up more than five hundred AI services in use and more than three in four employees reaching for unapproved tools.

The demand evidence is current but self-reported. The shadow-AI and agent-sprawl framing matches what enterprise buyers search for in 2026, yet the freshest proof of that demand is Singulr's own discovery statistic and a launch claim of deployments in technology, finance, and healthcare. For a company whose whole pitch is measured proof, named testimonials exist but the absence of dated case studies, deployment scope, and measurable outcomes is the gap a buyer notices first. \[[s7](#profile-analysis-sources), [s5](#profile-analysis-sources), [s4](#profile-analysis-sources)\]

### Product Capabilities

The capability set spans discovery, governance, and testing. Singulr discovers the AI in use across homegrown LLM applications, public services, and embedded SaaS AI, then lets teams identify risky services, approve safe ones, and enforce usage policy. Agent Pulse adds a live inventory of every agent with a risk score and enforceable controls, plus policy by agent type, data sensitivity, and tool access.

The differentiating work sits in agent runtime governance and continuous testing rather than discovery alone. The platform maps agentic dependencies, validates dataset licensing, and runs application-aware AI red teaming continuously against OWASP LLM Top 10, NIST, and MITRE scenarios wired into CI/CD. That said, no public technical architecture, demo recording, or independently inspectable benchmark appears in fetched sources, so the depth rests on marketing pages until a technical proof point appears. \[[s7](#profile-analysis-sources), [s3](#profile-analysis-sources), [s2](#profile-analysis-sources)\]

### Competitive Positioning

Singulr competes in the crowded AI governance and posture category, where it is one of several seed-stage vendors discovering shadow AI and governing enterprise AI usage. Olakai, which names Singulr as a competitor, centers ROI measurement while Singulr centers agent runtime governance, and Zenity overlaps the agent-governance core directly.

The position Singulr argues is the agentic control plane, deeper into runtime agent behavior than discovery-only tools. Whether that holds depends on staying ahead of cloud-security and AI-platform vendors that are adding AI discovery and policy as a feature for buyers they already serve, since the discovery layer alone is the most replicable part of the offer. \[[s1](#profile-analysis-sources), [s3](#profile-analysis-sources), [s9](#profile-analysis-sources)\]

### Go-to-Market & Traction

Singulr runs a sales-led enterprise motion fronted by its founders. The site routes every visitor to a demo request rather than a self-service trial, partner and customer portals exist, and the public voice of the company is the CEO through the launch press, the stage-appropriate motion for a seed-stage vendor selling a control decision.

The traction in the public record is indirect. The launch claims deployments across three regulated sectors, Dell and Nexus backing signals confidence, and the site now names customer testimonials and integrations, but those lack dated case studies and verifiable metrics and no marketplace listing appears in fetched sources. The founders still have to turn early deployments into reference accounts a skeptical buyer can call. \[[s4](#profile-analysis-sources), [s6](#profile-analysis-sources), [s7](#profile-analysis-sources)\]

### Team & Credibility

The founders carry a matched-domain credential most young vendors lack. Shiv Agarwal, the CEO, and Abhijit Sharma, the CTO, previously co-founded Arkin Net, a network virtualization and security company acquired by VMware, so the pair has built and exited in security infrastructure before. Selling governance to security and IT leadership sits squarely inside that experience.

The bench under the founders is not described in fetched sources, and the about page presents only the two co-founders. The investor backing is a team multiplier, since Nexus Venture Partners and Dell Technologies Capital led the seed and Dell's interest in enterprise infrastructure fits the platform's buyer, though backing does not substitute for the verifiable reference accounts the record still lacks. \[[s6](#profile-analysis-sources), [s4](#profile-analysis-sources)\]

### Trust Readiness

Singulr displays the attestations a security buyer expects at the seed stage. The company page carries certification badges for ISO/IEC 27001:2022 and AICPA SOC, alongside HIPAA and GDPR alignment marks, and Agent Pulse promises auditable records of agent actions and policy enforcement for internal and industry-specific requirements.

The attestations are self-displayed badges rather than inspectable reports in fetched sources. The ISO 27001 and SOC marks are commercial certifications that signal baseline hygiene, and no public trust portal or audit report appears to confirm what they cover. The HIPAA and GDPR marks describe alignment the platform helps customers meet, not an authorization Singulr itself holds. \[[s8](#profile-analysis-sources), [s3](#profile-analysis-sources), [s7](#profile-analysis-sources)\]

### Competitors

| Company | Relationship | Note |
|---|---|---|
| Olakai | competes with | Both discover shadow AI and govern enterprise AI usage, though Olakai centers ROI measurement while Singulr centers agent runtime governance. |
| Zenity | competes with | Zenity governs and secures AI agents and copilots, overlapping Singulr's agent-governance core. |
| Vorlon | adjacent | Vorlon governs non-human and AI identities and runtime data exposure, adjacent to Singulr's agent-identity and runtime-data coverage. |

## Strategy Deep Dive

A closer look at the company's product strategy, measuring how [defensible](https://zeltser.com/scoring-security-product-strategy) it is against market forces and examining the [eight areas](https://zeltser.com/security-product-creation-framework) behind it.

### Defensibility

**Exposed (12/21)**

Band guidance: pivot urgently. Analyzed 2026-09-11. Scope: whole company.

Singulr is durable where its problem is hard and exposed where its offer looks like software. Its agent runtime governance and continuous red teaming against OWASP, NIST, and MITRE attack scenarios are real systems work whose replication difficulty the record leaves unbenchmarked, and the accumulating AI inventory, agent policies, and risk records build switching friction once a customer embeds them. The discovery-and-policy core is weaker, since cloud-security and AI-platform vendors can add it as a feature. The ISO and SOC marks are commercial badges, not a regulatory lock, and the Pulse feed is vendor-claimed, not a proven corpus. It is harder to displace where a buyer leans on the runtime-governance depth, and easier to substitute where its discovery overlaps what rival Olakai sells.

| Dimension | Score | Rationale |
|---|---|---|
| Value Delivery | 1/3 | Customers buy software they configure and run, an AI inventory, risk scores, policy enforcement, and red-team scans, with no managed service or accountability layer the company stands behind in fetched sources. \[[s3](#deep-dive-sources), [s2](#deep-dive-sources)\] |
| Switching Cost | 2/3 | Accumulated AI inventories, agent policies, risk records, and dataset-licensing records create real embedding friction once a customer relies on them. No network effect, cross-customer asset, or residency lock appears in fetched sources. \[[s3](#deep-dive-sources), [s2](#deep-dive-sources), [s9](#deep-dive-sources)\] |
| Compliance Moat | 1/3 | ISO 27001:2022 and AICPA SOC are self-displayed marks, and the record shows no federal authorization or regulatory mandate for this product class. The HIPAA and GDPR marks appear under the same certifications heading with no fetched definition of what they certify, and they are not a moat that blocks replacement. \[[s10](#deep-dive-sources), [s9](#deep-dive-sources)\] |
| Problem Complexity | 3/3 | Continuous agent runtime governance with configuration and drift tracking, plus application-aware AI red teaming run continuously against OWASP LLM Top 10, NIST, and MITRE scenarios in CI/CD, is adversarial real-time systems work, though the record offers no benchmark or architecture from which to judge replication difficulty. \[[s2](#deep-dive-sources), [s4](#deep-dive-sources)\] |
| Buyer Profile | 2/3 | The launch reports deployments across technology, finance, and healthcare companies, and named customer testimonials exist, but no independently verified procurement detail or contractual deployment scope appears in fetched sources. \[[s5](#deep-dive-sources), [s8](#deep-dive-sources), [s1](#deep-dive-sources)\] |
| Layer | 2/3 | The platform spans the customer's AI estate and enforces policy and agent controls across it, which is more than a point application. No other software depends on Singulr to function, so it is not infrastructure. \[[s3](#deep-dive-sources), [s8](#deep-dive-sources)\] |
| Proprietary Data, Content, or IP | 1/3 | Per-tenant AI inventories, agent risk scores, and a catalog of AI tools appear in the record, which does not establish their tenancy or a cross-customer pooled corpus, and the Pulse intelligence the control-plane page names is not detailed enough to credit as a licensed dataset. \[[s6](#deep-dive-sources), [s8](#deep-dive-sources)\] |

### Strategic Market Segmentation

Singulr targets the enterprise where AI adoption has outrun control, and it names the buyer precisely. The site carries solution pages for the CISO and security team, the CIO and IT operations, and privacy and risk, so the company sells to the three offices that argue over who owns AI risk. The launch frames the pain in numbers a buyer recognizes, since live environments turn up more than five hundred AI services in use and more than three in four employees reaching for unapproved tools.

The segmentation leans top-down toward the budget owner rather than the practitioner. Every solution page addresses an executive function, and nothing in fetched sources shows a developer community or a bottoms-up adoption motion. That fits a governance story sold to security and IT leadership, where the purchase is a control decision rather than a tool a team picks up on its own.

The demand evidence is current but self-reported. The shadow-AI and agent-sprawl framing tracks the demand statistics the homepage cites, yet the demand evidence now pairs externally attributed 2025 statistics with Singulr's own discovery statistic and a launch claim of deployments in technology, finance, and healthcare. For a company whose whole pitch is measured proof, named testimonials exist but the absence of dated case studies, deployment scope, and measurable outcomes is the gap a buyer notices first. \[[s8](#deep-dive-sources), [s6](#deep-dive-sources), [s5](#deep-dive-sources), [s1](#deep-dive-sources)\]

### Product Capabilities & AI Advantages

The capability set is specific and spans discovery, governance, and testing. Singulr discovers the AI in use across homegrown LLM applications, public services, and embedded SaaS AI, then lets teams identify risky services, approve safe ones, and enforce usage policy. Its agent-runtime module maintains a live, risk-scored inventory of every agent and enforces guardrails that vary with the agent's role and the sensitivity of the data and tools it touches, while tracking configuration and runtime drift.

The differentiating work sits in agent runtime governance and continuous testing rather than discovery alone. The platform maps agentic dependencies, validates dataset licensing, and runs application-aware AI red teaming continuously against OWASP LLM Top 10, NIST, and MITRE scenarios wired into CI/CD. That adversarial, in-pipeline testing is harder systems work than reconciling usage data, and it is the part of the offer least like a reporting dashboard.

What is demonstrated rather than asserted is thin in the public record. No public technical architecture or independently inspectable benchmark appears in fetched sources, a platform overview video rides only in page metadata, and the named industry-recognition references are not available as technical evidence here, so the capability claims rest on marketing pages and the launch announcement. A buyer would have to take the red-teaming and runtime-enforcement depth on the vendor's word until a technical proof point appears. \[[s8](#deep-dive-sources), [s3](#deep-dive-sources), [s4](#deep-dive-sources), [s2](#deep-dive-sources)\]

### Sales Engagement & Go-to-Market

Singulr runs a sales-led enterprise motion fronted by its founders. The site routes every visitor to a demo request rather than a self-service trial, a partner portal exists, named customer testimonials appear on the homepage and product pages, and the public voice of the company is the CEO through the launch press. That is the stage-appropriate motion for a seed-stage vendor selling a control decision to security and IT leadership.

Distribution assets a copycat could not quickly assemble are not yet visible. A partner program is live and the site names integrations and carries partner testimonials separate from the customer ones, but no cloud marketplace listing appears in fetched sources and the commercial depth and channel scale of those partners are not quantified, so the reach today is direct selling plus early partners. The integration surface the platform consumes, across public AI services, homegrown apps, and embedded SaaS AI, is real engineering but the kind a funded competitor replicates by writing software.

The open question for the motion is conversion to named references. The launch claims deployments across three regulated sectors and the site now carries named customer testimonials, but the founders still have to turn those into detailed case studies and reference accounts with verifiable metrics that a skeptical buyer can call. Until then the GTM rests on founder credibility and investor signaling rather than proof a peer can verify. \[[s5](#deep-dive-sources), [s7](#deep-dive-sources), [s8](#deep-dive-sources), [s1](#deep-dive-sources), [s3](#deep-dive-sources)\]

### Pricing Model

Singulr publishes no pricing, and the unit it charges by is undisclosed. No fetched page shows a list price, a tier, or whether the company charges by AI service discovered, by agent governed, by seat, or by a share of the AI estate. The demo-only front door fits a vendor negotiating large enterprise deals rather than courting self-service buyers.

The pricing unit will reveal what Singulr believes buyers pay for. Charging by the number of agents or AI services governed would track the growth of the problem the platform measures, while a flat platform fee would decouple price from that sprawl. Fetched sources do not show which model the company chose, so the strategic signal pricing usually sends is not yet readable.

The cost of the continuous red teaming is a buyer's question the public record leaves open. Running application-aware red teaming continuously against multiple attack frameworks consumes compute, and no fetched page describes usage limits, included scan volume, or how that cost is bounded. A buyer evaluating the platform would want to know whether heavy testing carries a metered cost. \[[s2](#deep-dive-sources), [s8](#deep-dive-sources)\]

### Product Delivery & Operations

Singulr presents discovery-first onboarding, and the cited pages do not state the hosting model. The platform connects to the AI a company already uses, across homegrown applications, public services, and embedded SaaS AI, and surfaces contextual detail on settings, user activity, and sensitive data. The launch announcement claims the platform integrates into enterprise environments without requiring infrastructure changes, and no fetched page describes how each AI service or agent gets connected.

Agent runtime governance is the operationally heavier part of the offer. Enforcing controls on live agents and tracking configuration and runtime drift implies an in-environment enforcement path that has to keep pace as agents change, which is more demanding than periodic discovery. Fetched sources describe the capability but not the deployment architecture, agent coverage limits, or where enforcement sits relative to the agent runtime.

The delivery details a security reviewer would ask for are not yet public. No fetched page describes hosting regions, data residency options, a public API, or a status page, and the company runs from offices in Palo Alto and Pune without a published description of where customer data lives. For a platform that ingests AI usage and agent activity across the enterprise, those gaps are the questions procurement raises early. \[[s8](#deep-dive-sources), [s4](#deep-dive-sources), [s3](#deep-dive-sources), [s5](#deep-dive-sources)\]

### Earning Customers' Trust

Singulr displays the attestations a security buyer expects at the seed stage. The company page carries certification badges for ISO/IEC 27001:2022 and AICPA SOC, alongside HIPAA and GDPR marks, and Agent Pulse promises auditable records of agent actions, data access, and policy enforcement for internal and industry-specific requirements. The posture reads as one assembled for enterprise procurement rather than retrofitted later.

The attestations are self-displayed badges rather than inspectable reports in fetched sources. The ISO 27001 certification and SOC 2 attestation marks signal baseline security hygiene, and no public trust portal, audit report, or scope statement appears in the fetched record to confirm what they cover. The HIPAA and GDPR marks appear under the same certifications heading, and the fetched record does not define what those two marks certify.

The practice-what-you-preach test is structural for this product. Singulr warns enterprises that AI tools leak sensitive data while its own platform ingests AI usage, prompts context, and agent activity across the estate, so its own data handling has to clear the bar its marketing sets. The auditable-records design shows the company understands the expectation, and a regulated buyer will still ask for the report behind each badge. \[[s10](#deep-dive-sources), [s9](#deep-dive-sources), [s8](#deep-dive-sources)\]

### Platform Strategy & Ecosystem Positioning

Singulr positions itself as a control plane, and the architecture partly backs the claim. Three modules, discovery, agent governance, and AI risk and compliance, feed one platform that holds the AI inventory, risk records, and policies, so each new connected source makes the central record more complete. That is the compounding pattern of a platform rather than a bundle of point tools.

The ecosystem around the platform is one-directional so far. Singulr consumes data from many AI providers and SaaS applications, but no fetched source shows anyone building on Singulr, no public API documentation exists, and no marketplace presence appears. The homepage names integrations including Splunk, CrowdStrike, Zscaler, Okta, and Microsoft Entra alongside the partner program, though their depth is not visible in the fetched record.

Platform status will depend on becoming the system of record for AI decisions. The accumulated inventory, agent policies, and risk and dataset-licensing records are the assets that could make Singulr the place an enterprise decides which AI to keep, govern, or block. The marketing claims that position, and no verifiable case study or independent third party in fetched sources yet confirms it. \[[s2](#deep-dive-sources), [s3](#deep-dive-sources), [s8](#deep-dive-sources)\]

### Team & Execution Capability

The founders carry a credential matched to the domain they now sell into. Shiv Agarwal, the CEO, and Abhijit Sharma, the CTO, previously co-founded Arkin Net, a network virtualization and security company acquired by VMware, so the pair has built and exited in security infrastructure before. Selling governance to security and IT leadership sits inside that experience rather than adjacent to it.

The bench under the founders is not described in fetched sources. The about page now names Richard Bird as Chief Security Officer and Draeger Valencia in growth leadership alongside the two co-founders, though engineering depth and headcount stay undisclosed, so the full size of the team behind a three-module platform is not visible. The company is hiring, since the about page recruits for the control-plane build, which is consistent with an early team still scaling.

The investor backing is a team multiplier and a signal. Nexus Venture Partners and Dell Technologies Capital led the ten million dollar seed, and Dell's strategic interest in enterprise infrastructure fits the platform's buyer. That backing gives a small founding team reach and credibility with enterprise buyers, though it does not substitute for the verifiable reference accounts the public record still lacks. \[[s7](#deep-dive-sources), [s5](#deep-dive-sources), [s10](#deep-dive-sources)\]

## Sources

### Company Detail Sources

Cited from the Sourced Details and Matrix Coverage rows.

| Id | Source | Tier | Accessed |
|---|---|---|---|
| f1 | [Singulr AI homepage](https://singulr.ai/) | official | 2026-06-21 |
| f2 | [Singulr AI launch announcement (PR Newswire, February 18 2025)](https://singulr.ai/news-events/singulr-ai-launch) | official | 2026-06-21 |
| f3 | [SecurityWeek: Singulr Launches With $10M in Funding for AI Security and Governance Platform](https://www.securityweek.com/singulr-launches-with-10m-in-funding-for-ai-security-and-governance-platform/) | press | 2026-06-21 |
| f4 | [Singulr Agent Pulse product page](https://singulr.ai/products/agent-pulse) | official | 2026-06-21 |

### Profile Analysis Sources

Cited from the Market Readiness section.

| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | [Singulr AI homepage](https://singulr.ai/) “The Enterprise AI and Agentic Control Plane that closes the gap between AI policy and runtime reality.” | official | 2026-06-21 |
| s2 | [Singulr AI homepage core capabilities](https://singulr.ai/) “Map agentic dependencies, validate dataset licensing, and track risk records across their full lifecycle. Application-aware AI red teaming runs continuously against OWASP LLM Top 10, NIST, and MITRE scenarios, built into CI/CD, not bolted on after deployment.” | official | 2026-06-21 |
| s3 | [Singulr Agent Pulse product page](https://singulr.ai/products/agent-pulse) “Agent Pulse gives you a live inventory of every agent, their risk score, and enforceable controls so you can ensure that agents are working within your acceptable AI use boundaries.” | official | 2026-06-21 |
| s4 | [Singulr AI launch announcement (PR Newswire, February 18 2025)](https://singulr.ai/news-events/singulr-ai-launch) “Singulr AI launched today with the general availability of its enterprise AI governance and security platform, already deployed across companies in the technology, finance, and healthcare sectors.” | official | 2026-06-21 |
| s5 | [Singulr AI launch demand evidence](https://singulr.ai/news-events/singulr-ai-launch) “In live customer environments, Singulr consistently discovers 500+ unique AI services and models in use, with many of them redundant. Over three out of four employees use unapproved Shadow AI tools, often linked to personal accounts that expose enterprise IP.” | official | 2026-06-21 |
| s6 | [SecurityWeek: Singulr Launches With $10M in Funding for AI Security and Governance Platform](https://www.securityweek.com/singulr-launches-with-10m-in-funding-for-ai-security-and-governance-platform/) “Singulr AI was founded by Shiv Agarwal and Abhijit Sharma, who previously co-founded Arkin Net, a network virtualization and security firm that was acquired by VMware. The company has raised $10 million in seed funding from Nexus Venture Partners, Dell Technologies Capital and industry executives.” | press | 2026-06-21 |
| s7 | [SecurityWeek: Singulr platform capabilities and offices](https://www.securityweek.com/singulr-launches-with-10m-in-funding-for-ai-security-and-governance-platform/) “With offices in Palo Alto, California, and Pune, India. The platform enables customers to discover every generative AI and obtain information on its use within the organization, identify risky AI services, approve safe AI services, and enforce policies and rules regarding the use of AI.” | press | 2026-06-21 |
| s8 | [About Singulr company page certifications](https://singulr.ai/about/company) “CERTIFICATIONS ISO/IEC 27001:2022 AICPA SOC. Health Insurance Portability and Accountability Act. General Data Protection Regulation.” | official | 2026-06-21 |
| s9 | [Olakai homepage (cited competitor)](https://olakai.ai/) | other | 2026-06-21 |

### Deep-Dive Sources

Cited from the Strategy Deep Dive section.

| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | [Singulr AI homepage](https://singulr.ai/) “The Enterprise AI and Agentic Control Plane that closes the gap between AI policy and runtime reality.” | official | 2026-06-21 |
| s2 | [Singulr AI homepage core capabilities](https://singulr.ai/) “Map agentic dependencies, validate dataset licensing, and track risk records across their full lifecycle. Application-aware AI red teaming runs continuously against OWASP LLM Top 10, NIST, and MITRE scenarios, built into CI/CD, not bolted on after deployment.” | official | 2026-06-21 |
| s3 | [Singulr Agent Pulse product page](https://singulr.ai/products/agent-pulse) “Agent Pulse gives you a live inventory of every agent, their risk score, and enforceable controls so you can ensure that agents are working within your acceptable AI use boundaries.” | official | 2026-06-21 |
| s4 | [Singulr Agent Pulse governance](https://singulr.ai/products/agent-pulse) “Define enforceable policies based on agent type, data sensitivity, tool access, and scope. Track agent configuration and run time drift.” | official | 2026-06-21 |
| s5 | [Singulr AI launch announcement (PR Newswire, February 18 2025)](https://singulr.ai/news-events/singulr-ai-launch) “Singulr AI launched today with the general availability of its enterprise AI governance and security platform, already deployed across companies in the technology, finance, and healthcare sectors.” | official | 2026-06-21 |
| s6 | [Singulr AI launch announcement demand evidence](https://singulr.ai/news-events/singulr-ai-launch) “In live customer environments, Singulr consistently discovers 500+ unique AI services and models in use, with many of them redundant. Over three out of four employees use unapproved Shadow AI tools, often linked to personal accounts that expose enterprise IP.” | official | 2026-06-21 |
| s7 | [SecurityWeek: Singulr Launches With $10M in Funding for AI Security and Governance Platform](https://www.securityweek.com/singulr-launches-with-10m-in-funding-for-ai-security-and-governance-platform/) “Singulr AI was founded by Shiv Agarwal and Abhijit Sharma, who previously co-founded Arkin Net, a network virtualization and security firm that was acquired by VMware. The company has raised $10 million in seed funding from Nexus Venture Partners, Dell Technologies Capital and industry executives.” | press | 2026-06-21 |
| s8 | [SecurityWeek: Singulr platform capabilities and offices](https://www.securityweek.com/singulr-launches-with-10m-in-funding-for-ai-security-and-governance-platform/) “With offices in Palo Alto, California, and Pune, India. The platform enables customers to discover every generative AI and obtain information on its use within the organization, identify risky AI services, approve safe AI services, and enforce policies and rules regarding the use of AI.” | press | 2026-06-21 |
| s9 | [Singulr Agent Pulse compliance records](https://singulr.ai/products/agent-pulse) “Agent Pulse provides auditable records of agent actions, data access, and policy enforcement for internal requirements and industry-specific regulations.” | official | 2026-06-21 |
| s10 | [About Singulr company page certifications](https://singulr.ai/about/company) “CERTIFICATIONS ISO/IEC 27001:2022 AICPA SOC. Health Insurance Portability and Accountability Act. General Data Protection Regulation.” | official | 2026-06-21 |
| s11 | [Singulr AI Control Plane product page](https://singulr.ai/products/ai-control-plane) | official | 2026-06-21 |
| s12 | [Olakai homepage (cited competitor)](https://olakai.ai/) | other | 2026-06-21 |

## Disclaimer

This site is an experimental research aid created by Zeltser Security Corp. All its data gathering and analysis was performed autonomously without human review, and it can contain errors of fact, interpretation, and judgment that a human reviewer might catch.

The analyses are statements of opinion, not statements of fact. Machine analysis produced the scores, summaries, and matrix placements by weighing the public sources each page cites, and reasonable people can weigh the same sources differently. Where a page states a fact, it cites the public source and the date it was checked, and the statement is only as accurate as that source. Unless a profile expressly says otherwise, the analysis involves no hands-on testing and no independent validation of any company's products or services.

Nothing here is professional, security, legal, financial, investment, or purchasing advice, and nothing here is a recommendation to invest in, do business with, or avoid any company. Inclusion of a company is not an endorsement, and absence of a company is not a judgment about it. Reading this site creates no advisory or client relationship. Verify any detail you plan to act on against the vendor's current materials.

The content is provided "as is" and "as available," with all warranties disclaimed, express or implied, including merchantability, fitness for a particular purpose, accuracy, and non-infringement. No entry is warranted to be complete, current, or correct. Companies change, vendors update their claims, sources can be wrong, and automated analysis can misread them.

To the fullest extent permitted by law, the operator, Zeltser Security Corp, is not liable for any damages that arise from using this site or relying on its content, including direct, indirect, incidental, special, and consequential damages and lost profits, even if advised that such damages were possible. If you are dissatisfied with the site or disagree with these terms, your remedy is to stop using it.

Entries link to vendor pages, press coverage, and other external sites that Zeltser Security Corp does not control and is not responsible for. A link is not an affiliation with the destination or an endorsement of it. Product and company names and trademarks are the property of their owners, used here nominatively to identify the companies described. Short quotations from cited sources appear for identification and commentary.

Use, quotation, automated retrieval, and redistribution of the content are governed by the Terms of Use at cybercompanyprofiles.com/terms, which permit personal and internal business use with attribution and prohibit republication and resale.